by Mia Taylor
Last updated: 7:47 PM ET, Thu October 26, 2017
When it comes time to plan a vacation, travelers often book their airfare first and then begin the process of identifying a hotel in their chosen destination.
A new booking tool from the online travel agency Hopper may change that approach.
The site, which previously focused on providing information about the ups and downs of airfare, announced a new hotel price prediction service that, among other things, helps users track accommodation prices and forecasts whether rates are likely to rise or fall.
"We're taking all of the things you love about Hopper for flights -- guidance, reliability, easy-to-use mobile experience -- and bringing it to hotels, so you'll never to need wonder again whether you got a good deal on your room or if you should've waited for a better price," the company said in a statement.
In developing the new app, Hopper has determined the best time to book a hotel is not just before your trip, but rather two to three months in advance.
Similar to monitoring flights months in advance, you may also want to start monitoring hotels in order to get the best deal. To help you do that, Hopper will keep tabs on hotel prices 24-hours a day, seven days a week and alert you when to book.
"We found that maybe travelers don't feel the same anxiety about hotel prices changing as they do with flights, but there's actually a lot of price variability and the savings potential can be much greater with hotels," Frederic Lalonde, the company's founder and chief executive, told TravelPulse.
Hopper claims its accommodation prediction service is 95 percent accurate up to six months before your planned getaway.
The launch of the predictive hotel offering is the biggest step forward Hopper has taken since unveiling its mobile app two years ago, which has since been downloaded 17 million times.
"We've sold over $500 million worth of airfare and tracked over 45 million trips," Lalonde said. "Our average trip watch is for eight days, which means that could be as much as 360 million room nights, so it seemed natural for us to continue the conversation we're having with users via push to help them also plan their stay."
In order to provide users with price predictions for hotels, Hopper developed an algorithm that takes into account such things as qualitative and quantitative data, customer reviews and information regarding prices.
Hopper began collecting data for its new predictive hotel offering more than one year ago, Lalonde said. It now has 100 million data points for just New York City, covering prices at 600 hotels for the past 12 months and six months into the future.
The app has shown the potential to save users about $270 per week-long trip. As a comparison, Hopper's flight data saves users an average of $50 on domestic flights and $120 on international flights.
"This means you'll be able to leverage Hopper's technology for far more savings when it comes to hotels," Lalonde said during an interview with Bloomberg.
There do appear to be some growing pains to be ironed out for the new Hopper app, however. Bloomberg did some initial beta testing of the hotel feature, which promises to show only the lowest hotel prices and found that wasn't always the case.
The Hopper app, for instance, listed a room at New York's Knickerbocker for $264. But that same room was available for $223 on the hotel's website, Priceline.com and Booking.com. Yet the Hopper app stated "Prices won't get lower. Book now."
Lalonde told TravelPulse that the site is making some optimizations to ensure that it always offers parity with competitors.
Hopper's predictive accommodation feature currently offers information on about 25 properties in New York City. The plan is to expand beyond that footprint to include more listings in New York and to branch out nationally to such places as San Francisco, Los Angeles, and Miami in early 2018.
"We're focused on providing a highly curated set of hotels because we believe it's a better experience on mobile," Lalonde said. "We predominately cater to millennials so we only want to include standout properties, in terms of quality, price and vibe or atmosphere."
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